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A METHOD FOR CONVERTING A SMILING FACE TO A NEUTRAL FACE WITH APPLICATIONS TO FACE RECOGNITION
BibTeX
@MISC{Ramach_amethod,
author = {Mahesh Ramach and Shaohua Kevin Zhou and Divya Jhalani},
title = {A METHOD FOR CONVERTING A SMILING FACE TO A NEUTRAL FACE WITH APPLICATIONS TO FACE RECOGNITION},
year = {}
}
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Abstract
The human face displays a variety of expressions like smile, sorrow, surprise etc. All these expressions constitute nonrigid motions of various features of the face. These expressions lead to a significant change in the appearance of a facial image which leads to a drop in the recognition accuracy of a face-recognition system trained with neutral faces. There are other factors like pose and illumination which also lead to performance drops. Researchers have proposed methods to tackle the effects of pose and illumination; however, there has been little work on how to tackle expressions. In this work, we attempt to address the issue of expression invariant face-recognition. We present pre-processing steps for converting a smiling face to a neutral face. We expect that this would in turn make the vector in the feature space to be closer to the correct vector in the gallery, in an appearance-based face recognition. This conjecture is supported by our recognition results which demonstrate that the accuracy goes up if we include the expression-normalization block. 1.
Keyphrases
feature space present pre-processing step little work nonrigid motion performance drop surprise etc neutral face expression invariant face-recognition facial image recognition accuracy recognition result appearance-based face recognition various feature face-recognition system human face significant change correct vector expression-normalization block
